Control tolerante a fallos en comunidades energéticas basado en blockchain

[EN] This work describes a distributed control system that optimizes energy management using model predictive control in an energy community. The system has been extended to provide each agent with a fault-tolerant mechanism capable of detecting, isolating, and reconfiguring agents in case of failur...

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Detalles Bibliográficos
Autores: Sivianes, Manuel, Velarde, Pablo, Zafra-Cabeza, Ascensión, Bordons, Carlos
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:español
OAI Identifier:oai:riunet.upv.es:10251/222708
Acceso en línea:https://riunet.upv.es/handle/10251/222708
Access Level:acceso abierto
Palabra clave:Energy systems
Predictive control
Decentralized control
Fault-tolerant
FDI for linear systems
Sistemas energéticos
Control predictivo
Control descentralizado
Tolerante a fallos
Detección y diagnóstico de fallos para sistemas lineales
Descripción
Sumario:[EN] This work describes a distributed control system that optimizes energy management using model predictive control in an energy community. The system has been extended to provide each agent with a fault-tolerant mechanism capable of detecting, isolating, and reconfiguring agents in case of failures. Fault detection involves the calculation of residual signals and probability-based thresholds that minimize false positives. Once a fault is identified, reconfiguration is performed by adjusting the parameters of the agent s predictive controller to bring the system to an acceptable level of safety. If the  reconfiguration affects more than one agent, the information must be shared with the other agents. The control algorithm relies on a smart contract on a blockchain network, enabling the problem to be solved in a distributed manner without a centralized coordinator, while ensuring the security and integrity of the data. The proposed control strategy has been evaluated through various simulations in an energy community.